Abstract
As a result of the worldwide depletion of natural resources, increased energy use, and environmental, economic, and social imbalance, organizations are working to identify the proper strategies supporting the continuous reduction of their impacts. While this trend is fundamentally agreed upon in the literature, several manufacturing industries still fail to identify which elements most influence their contributions to the impact of sustainability and how to easily manage the calculation of these effects within a manufacturing system. The purpose of this article is to incorporate sustainability practices into manufacturing by developing a set of key performance indicators (KPIs) for assessing and improving environmental and economic management practices at the corporate and production level. The definition of the framework began with in-depth research of the leading indicators and framework types in the literature, integrating the most exploited industrial standards to make them easily acceptable in the industrial domain. Then, to provide a broad view of company behavior, the framework has been designed to take either an inventory and impact point of view, thus providing indicators for the online monitoring of the company operations, or assessing their impacts in an LCA-LCC perspective. In selecting the indicators and the definition of the framework structure, five industrial cases covering different business sectors were involved in identifying the most critical indicators in terms of calculability and defining a structure that would allow for their application in various business situations. Therefore, the defined framework has been validated at a conceptual level, thus laying the basis for future quantitative validation. Twenty key performance indicators (KPIs) for assessing the sustainability of manufacturing firms have been created based on the 163 indicators studied.
Highlights
The growing introduction of sustainability enablers for manufacturing, such as Industry 4.0 software, internet of things (IoT), and big data analytics in the industrial domain is paving the way for structuring data rich environments, in addition to energy modeling approaches that exploit continuous data collection for automated model learning can be defined
Framing our research in this context, we focused on the analysis of the indicators and frameworks which follow the three main drivers of our research: being exploitable at the company level, having a focus on processes more than on products, and showing a special emphasis on energy consumption
The results showed that the majority of the framework considered the sustainability paradigm, but lacked integration with the decisional paradigm, which is critical for a successful sustainability implementation project
Summary
The purpose of this article is to incorporate sustainability practices into manufacturing by developing a set of key performance indicators (KPIs) for assessing and improving environmental and economic management practices at the corporate and production level. Considering the concept of industry ecology [24], the purpose of this research is to integrate sustainability practices into manufacturing processes by providing a set of key performance indicators (KPIs) for evaluating and improving environmental and economic management practices at the corporate and production levels. We aim to fill this identified gap by defining a comprehensive framework integrating inventory and impact indicators meant to meet the industrial needs in terms of comprehensiveness of the analysis and usability of the developed set. The final goal of this paper was to develop a framework to support companies in assessing manufacturing activities using an inventory and impact perspective by retaining a corporate and production level view
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